1 / 42

Remote Sensing of Precipitation

Remote Sensing of Precipitation. Remote Sensing of Clouds and Water Vapor NWS WSR-88D NEXRAD METEK MicroRainRadar TRMM Satellite-based Radar Northwest Flow Snowfall Studies For Next Class: Read rest of Chapter. GOES-East Visible. GOES-East Thermal Infrared.

cheng
Download Presentation

Remote Sensing of Precipitation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Remote Sensing of Precipitation • Remote Sensing of Clouds and Water Vapor • NWS WSR-88D NEXRAD • METEK MicroRainRadar • TRMM Satellite-based Radar • Northwest Flow Snowfall Studies For Next Class: Read rest of Chapter

  2. GOES-East Visible GOES-East Thermal Infrared GOES-East Images of the United States and Portions of Central America on April 17, 1998 GOES-East Water Vapor Jensen, 2000

  3. Cloud Type Determination Based on Multispectral Measurements in the Visible and Thermal Infrared Regions of the Spectrum Thermal Infrared Jensen, 2000

  4. NEXRAD WSR-88D • Radar is used widely to analyze the temporal and spatial characteristics of precipitation • NEXRAD (Next Generation of Weather Radar) are operated by the National Weather Service • Provide high spatial and temporal resolution • Effective in detecting severe storms and even tornadoes • Have algorithms to estimate total precipitation

  5. Volume Coverage Pattern for Precipitation • Allows for rapid sampling of a range of elevations • Can be further accelerated for severe mode

  6. KMRX – 1318Z

  7. KGSP – 1317Z

  8. NW-SE Cross Section – 18Z Moisture Over and West of the Mountains NC Mountains

  9. METEK Inc. Radar in Scholls, OR Ku-band (1.25 cm wavelength) Cost ~ $40K Resolution  150 m Measurements of: • Doppler velocity • dBZ- attenuates in moderate to heavy rain

  10. Microphysical and Observational Context Fall velocity Radar reflectivity Snow Layer 0C Melting Layer Rain Layer Vertically-pointing radar Ground Surface

  11. Variable freezing level Height (m) m/s dBZ UTC Time (hours) UTC Time (hours)

  12. TRMM Precipitation Radar (PR) data obtained on March 9, 1998 A B 10 0 20 40 60 z(dBZ) 5 Height (km) A B 100 200 300 400 Distance (km) Along-track cross-section of TRMM Precipitation Radar data obtained on March 9, 1998 Jensen, 2000

  13. Synoptic Patterns Responsible for Snowfall

  14. A “Typical” NWFS Event: 10-11 Feb 2005 NWFS = Snowfall w/ 850 hPa NW (270-360°) Flow

  15. Rising Air Motions Sinking Air Motions

  16. 11 Feb 2006: Heavy NWFS

  17. Significant blowing and drifting of snow frequently occurs . . .

  18. Leading to sizeable drifts on roads even during light events

  19. Synoptic Ingredients of NWFS Perry (2006), Ph.D. Diss.

  20. Windward vs. Leeward Slopes in Periods of NWF Perry and Konrad (2006), Climate Research

  21. Accumulation During a Typical NWFS Event Perry and Lee (2007), Unpublished

  22. Annual Snowfall in the GSMNP, 1990-2004 Perry et al. (2007), Proceedings of the Eastern Snow Conference

  23. 57 48 1 5

  24. More Snow in the NC High Country

  25. No Snow in the NC High Country

  26. 25 Jan 2006 Radar 40+ cm in SE WV

  27. Collaborative Efforts with Dr. Sandra Yuter NW Flow

  28. MRR Summary: 17-19 Feb 2007 (5.5” snow, 0.24” swe, 23:1) WSR-88D Coverage Echo Tops < 6,000 ft

  29. MRR Summary: 17-19 Feb 2007 (5.5” snow, 0.24” swe, 23:1) 0.1” 0.01” 10:1 1.6” 0.09” 18:1 2.8” 0.12” 23:1 0.5” 0.01” 50:1 0.5” 0.01” 50:1

  30. MRR Summary: 15-16 Apr 2007 (4.4” snow, 0.48” swe, 9:1) WSR-88D Coverage

  31. MRR Summary: 15-16 Apr 2007 (4.4” snow, 0.48” swe, 9:1) 3.9” 0.40” 10:1 0.5” 0.08” 6:1 Graupel

  32. 2007-2013 Snow Season Activities • Model Analysis – Compare numerical model output (QPF, moist layer thickness, and moist layer temperature profiles) to observations on Poga Mountain; includes balloon releases (w/ D. Miller). • Snow Density – Relate snow density observations to meteorological parameters and develop guidelines for forecasting snow density (crucial for forecasting snowfall). • Spatial Patterns – Utilize a dense network of volunteer precipitation observers as part of the CoCoRaHS network to improve understanding of the spatial patterns of snowfall.

  33. MRR Summary: 27-29 Feb 2008 (8.3” snow, 0.39” swe, 21:1) WSR-88D Coverage

  34. Skew-T Plots

  35. MRR Summary: 1-2 Mar 2009 (11.1” snow, 0.94” swe, 12:1) 3.9” 0.40” 10:1 0.5” 0.08” 6:1 Graupel

  36. Byers 1965

  37. Libbrecht 2007

  38. Summary and Conclusions Spatial patterns of NWFS are strongly controlled by topography. Over 50% of mean annual snowfall at higher elevations and along windward slopes occurs in association with low-level NW flow. Antecedent upstream air trajectories with a Great Lakes connection help to enhance snowfall. Ongoing research on Poga Mt. in Flat Springs, NC, has highlighted the following: Shallow and convective nature of NWFS. Exceptional snow density variability. Dominance of NWFS

  39. Questions?

More Related